Abstract
Background
In Japan, emergency medical service (EMS) providers are prohibited from field termination-of-resuscitation (TOR) in out-of-hospital cardiac arrest (OHCA) patients. In 2013, we developed a TOR rule for emergency department physicians (Goto’s TOR rule) immediately after hospital arrival. However, this rule is subject to flaws, and there is a need for revision owing to its relatively low specificity for predicting mortality compared with other TOR rules in the emergency department. Therefore, this study aimed to develop and validate a modified Goto’s TOR rule by considering prehospital EMS cardiopulmonary resuscitation (CPR) duration.
Methods
We analysed the records of 465,657 adult patients with OHCA from the All-Japan Utstein registry from 2016 to 2019 and divided them into two groups: development (n = 231,363) and validation (n = 234,294). The primary outcome measures were specificity, false-positive rate (FPR), and positive predictive value (PPV) of the revised TOR rule in the emergency department for predicting 1-month mortality.
Results
Recursive partitioning analysis for the development group in predicting 1-month mortality revealed that a modified Goto’s TOR rule could be defined if patients with OHCA met the following four criteria: (1) initial asystole, (2) unwitnessed arrest by any laypersons, (3) EMS-CPR duration > 20 min, and (4) no prehospital return of spontaneous circulation (ROSC). The specificity, FPR, and PPV of the rule for predicting 1-month mortality were 99.2% (95% confidence interval [CI], 99.0–99.4%), 0.8% (0.6–1.0%), and 99.8% (99.8–99.9%), respectively. The proportion of patients who fulfilled the rule and the area under the receiver operating curve (AUC) was 27.5% (95% CI 27.3–27.7%) and 0.904 (0.902–0.905), respectively. In the validation group, the specificity, FPR, PPV, proportion of patients who met the rule, and AUC were 99.1% (95% CI 98.9–99.2%), 0.9% (0.8–1.1%), 99.8% (99.8–99.8%), 27.8% (27.6–28.0%), and 0.889 (0.887–0.891), respectively.
Conclusion
The modified Goto’s TOR rule (which includes the following four criteria: initial asystole, unwitnessed arrest, EMS-CPR duration > 20 min, and no prehospital ROSC) with a > 99% predictor of 1-month mortality is a reliable tool for physicians treating refractory OHCAs immediately after hospital arrival.
Supplementary Information
The online version contains supplementary material available at 10.1186/s13054-022-03999-x.
Keywords: Out-of-hospital cardiac arrest, Cardiopulmonary resuscitation, Termination-of-resuscitation rule, Emergency department, Outcome, Epidemiology
Background
The 2010 international consensus on cardiopulmonary resuscitation (CPR) and emergency cardiovascular care science with treatment recommendations (CoSTR) recommended validated termination-of-resuscitation (TOR) rules in the field for adult patients with out-of-hospital cardiac arrest (OHCA) [1, 2]. The TOR rules have been implemented to utilise hospital healthcare resources better, reduce hazards to emergency medical service (EMS) providers, and preserve patients’ dignity treatment is futile [3–5]. The 2020 CoSTR softens the recommendation: the use of TOR rules to assist clinicians in deciding whether to discontinue resuscitation efforts out of the hospital or to transport the patient to a hospital while ongoing CPR, taking into consideration the social acceptability of the potential survivors and the very limited clinical validation of such rules [6]. In some Asian countries, including Japan, no TOR rules in the field can be legally implemented, and it is mandated that all cardiac arrest patients be transported to the hospital [7–11]. Therefore, in 2013, we developed a TOR rule for emergency department physicians (Goto’s TOR rule [12]) immediately after patient arrival to the hospitals to better utilise hospital healthcare resources. The Goto’s TOR rule for deciding whether to withhold further resuscitation attempts or terminate ongoing resuscitation includes three criteria: no prehospital return of spontaneous circulation (ROSC), initial non-shockable rhythm, and unwitnessed arrest by bystanders. However, the Goto’s TOR rule has a relatively low specificity compared with other TOR rules in the emergency department [13, 14]. The American Heart Association (AHA) and European Resuscitation Council guidelines cautioned that prognostication for outcomes after cardiac arrest should be used very cautiously if the 95% confidence interval (CI) of a diagnostic test is between 90 and 95% because of its imprecision [15, 16]. Moreover, although a longer prehospital EMS-CPR duration is associated with unfavourable outcomes after OHCA [17, 18], there are no TOR rules immediately after hospital arrival, including prehospital EMS-CPR duration as a criterion. In this context, the Goto’s TOR rule should be modified to improve its accuracy by including the EMS-CPR duration in the TOR rule’s criteria.
In this study, using a nationwide population-based registry in Japan, we aimed to develop and validate a modified Goto’s TOR rule that would allow physicians to decide whether to terminate ongoing resuscitation efforts immediately after hospital arrival. Moreover, we validated the other TOR rules (Goto’s TOR [12], Korean Cardiac Arrest Research Consortium [KoCARC] I, [11] and III rules [11]) in the emergency department to compare the performance characteristics of a modified Goto’s TOR rule.
Methods
Study design and setting
This nationwide, population-based observational study included all adult patients (aged ≥ 18 years) who experienced OHCA and were resuscitated by EMS personnel between 1 January 2016 and 31 December 2019 in Japan. Patients were excluded based on the following criteria: (1) age < 18 years, (2) physician on board the ambulance, (3) unknown EMS-CPR duration, and (4) origin of cardiac arrest due to accidental hypothermia (Fig. 1). Since a paramedic EMS team staffed with no physician delivers prehospital care for OHCA in most parts of Japan, we excluded patients with a physician on board the ambulance [19]. However, for sensitivity analysis, we included patients with a physician on board the ambulance and those with unknown EMS-CPR duration during the study period of 2018–2019 as the sensitivity analysis group.
Fig. 1.
Flow chart of the patient inclusion criteria. CPR, cardiopulmonary resuscitation; EMS, emergency medical service
In Japan, the nationwide EMS system is supervised by the Fire and Disaster Management Agency (FDMA), while local fire stations operate local EMS systems. As of 2019, Japan has 726 fire departments and 5,215 ambulance teams [20]. All EMS personnel performed CPR according to the Japanese guidelines [21]. EMS personnel are permitted to use several resuscitation methods, including automated external defibrillators, airway adjuncts, peripheral intravenous catheters, and Ringer’s lactate solution administration. In the field, only specially trained emergency lifesaving technicians are permitted to insert a tracheal tube and administer intravenous adrenaline (epinephrine) upon receiving instructions from an online physician. EMS personnel in Japan are legally prohibited from terminating resuscitation. Since 2006, emergency telephone dispatchers in Japan have been required to provide instructions on how to perform compression-only CPR if it is challenging for bystanders to administer rescue breaths.
Data collection and quality control
The FDMA in Japan launched an ongoing, prospective, population-based observational study involving patients with OHCA who had received resuscitation from EMS personnel in 2005 [20]. In cooperation with the physician-in-charge, EMS personnel from each centre recorded the data of patients with OHCA using a Utstein-style template. The FDMA permitted access to the database and provided anonymous data for our analysis. Neurological outcomes were defined using the cerebral performance category (CPC) scale (category 1, good cerebral performance; category 2, moderate cerebral disability; category 3, severe cerebral disability; category 4, coma or vegetative state; and category 5, death) [22]. The physician-in-charge determined the CPC categorisation 1-month after cardiac arrest.
Study endpoints
The primary study endpoints were the specificity, false-positive rate (FPR), and positive predictive value (PPV) of a modified Goto’s TOR rule for predicting 1-month mortality and unfavourable neurological outcome (CPC scale categories 3–5). The secondary endpoints were those of other TOR rules in the emergency department (Goto’s TOR [12], KoCARC I [11], and III rules [11]) for predicting 1-month mortality and unfavourable neurological outcomes.
Statistical analysis
Continuous variables were expressed as medians (interquartile range, first to third quartiles), and categorical variables were expressed as percentages. As an estimate of effect size and variability, we reported the sensitivity, specificity, FPR, PPV, negative predictive value (NPV), and area under the receiver operating curve (AUC) of the TOR rules with 95% CIs. We selected seven prehospital variables (age, initially recorded rhythm, witnessed status, bystander CPR, prehospital shock delivery, duration of EMS-initiated CPR [EMS-CPR duration], and prehospital ROSC) as candidates for consideration of the modified TOR rules based on data from previous studies [11, 12, 17, 18, 23]. Using seven prehospital variables in the development group, we performed a recursive partitioning analysis to develop a modified Goto’s TOR rule in the emergency department to predict medically futile CPR (1-month survival rate of < 1% [4, 24, 25]) in patients with OHCA. Recursive partitioning analysis creates a branching decision tree by dividing the patient population into subgroups according to the results of an analysis of the relationship between outcome populations after OHCA and prehospital variables [7, 23, 26]. Fivefold cross-validation was used to assess the predictive ability of the decision tree model. We compared the performance of a modified Goto’s TOR rule with that of other rules (Goto’s TOR [12], KoCARC I [11], and III rules [11]) for predicting 1-month mortality or unfavourable neurological outcomes using the validation group. Sensitivity analysis was performed after mean value imputation of the missing value for EMS-CPR duration using the sensitivity analysis group. The sensitivity, specificity, FPR, PPV, and NPV between TOR rules were compared using McNemar’s test.
All statistical analyses were performed using the JMP statistical package version 15.2-Pro (SAS Institute Inc., Cary, NC, USA). All reported tests were two-tailed, and a P value of < 0.05 was considered statistically significant.
Results
Details of attempted resuscitations performed for 504,561 patients with OHCA between 2016 and 2019 were documented in the database. Ultimately, 465,657 patients (92.2% of registered patients) who experienced OHCA were eligible for analysis. Patients were divided into the development (2016–2017; n = 231,363) and validation groups (2018–2019; n = 234,294). Baseline characteristics of the study participants are presented in Table 1. The overall 1-month survival and CPC 1–2 rates were 6.1% and 3.7%, respectively.
Table 1.
Baseline characteristics of study participants
Characteristic | All patients | Development group | Validation group | |||
---|---|---|---|---|---|---|
(n = 465,657; 100%) | (n = 231,363; 49.7%) | (n = 234,294; 50.3%) | ||||
Age, years | 80 | (69–87) | 80 | (69–87) | 80 | (69–87) |
Male | 264,308 | (56.8) | 131,049 | (56.6) | 133,259 | (56.9) |
Witnessed arrest | 190,268 | (40.9) | 95,078 | (41.1) | 95,190 | (40.6) |
Rural area† | 111,327 | (23.9) | 55,709 | (24.1) | 55,618 | (23.7) |
Bystander CPR | 233,204 | (50.1) | 114,357 | (49.4) | 118,847 | (50.7) |
AED use by bystander before EMS arrival at the site | 7197 | (1.5) | 3551 | (1.5) | 3646 | (1.6) |
Initial shockable rhythm | 28,970 | (6.2) | 14,823 | (6.4) | 14,147 | (6.0) |
Presumed cardiac cause | 291,638 | (62.6) | 143,509 | (62.0) | 148,129 | (63.2) |
Use of advanced airway management | 183,267 | (39.4) | 90,272 | (39.0) | 92,995 | (39.7) |
Epinephrine administration | 103,539 | (22.2) | 45,468 | (19.7) | 58,071 | (24.8) |
Prehospital AED administration by EMS personnel | 43,399 | (9.3) | 21,829 | (9.4) | 21,570 | (9.2) |
EMS response time, min | 9 | (7–11) | 9 | (7–11) | 9 | (7–11) |
Prehospital EMS-initiated CPR duration, min | 22 | (17–28) | 22 | (17–28) | 22 | (17–28) |
Prehospital ROSC | 47,220 | (10.1) | 22,527 | (9.7) | 24,693 | (10.5) |
1-month survival | 28,574 | (6.1) | 13,934 | (6.0) | 14,640 | (6.3) |
1-month CPC 1–2 | 17,027 | (3.7) | 8270 | (3.6) | 8757 | (3.7) |
Values are reported as n (%) or medians (interquartile range [1st to 3rd quartiles])
AED, automated external defibrillator; CPC, Cerebral Performance Category; CPR, cardiopulmonary resuscitation; EMS, emergency medical service; ROSC, return of spontaneous circulation
†The rural area comprises 19 prefectures with a population of fewer than 200 inhabitants per km2
The result of recursive partitioning analysis for the development group in predicting 1-month mortality is depicted in Fig. 2, defined as patients with OHCA meeting all four of the following criteria: (1) initial asystole, (2) unwitnessed arrest (by bystanders or EMS providers), (3) EMS-CPR duration > 20 min, and (4) no prehospital ROSC. The results of the performance of the modified Goto’s rule in predicting 1-month mortality are shown in Table 2. In the development group, 27.5% (95% CI 27.3–27.6%) of patients fulfilled all four criteria and had a survival rate of 0.17% (95% CI 0.15–0.21%). In addition, the modified Goto’s TOR rule had a specificity of 99.2% (95% CI 99.0–99.4%), FPR of 0.8% (95% CI 0.6–1.0%), and PPV of 99.8% (95% CI 99.8–99.9%). In the validation group, 27.8% (95% CI 27.6–28.0%) of the patients met the four criteria and had a survival rate of 0.21% (95% CI 0.18–0.25%), specificity of 99.1% (95% CI 98.9–99.2%), FPR of 0.9% (95% CI 0.8–1.1%), and PPV of 99.8% (95% CI 99.8–99.8%).
Fig. 2.
Result of recursive partitioning analysis for predicting 1-month mortality in the development group. CPR, cardiopulmonary resuscitation; EMS, emergency medical service; ROSC, return of spontaneous circulation
Table 2.
Classification accuracy of modified Goto’s TOR rule for predicting 1-month mortality
Valuables | Development group (n = 231,363) | Validation group (n = 234,294) | ||
---|---|---|---|---|
Fulfilled 4/4 criteria | Did not fulfil criteria | Fulfilled 4/4 criteria | Did not fulfil criteria | |
(n = 63,528, 27.5%) | (n = 167,835, 72.5%) | (n = 65,104, 27.8%) | (n = 169,190, 72.2%) | |
Death, n | 63,417 | 154,012 | 64,967 | 154,687 |
Survival, n | 111 | 13,823 | 137 | 14,503 |
Survival rate (95% CI), % | 0.17 (0.15–0.21) | 8.24 (8.11–8.37) | 0.21 (0.18–0.25) | 8.57 (8.44–8.71) |
Sensitivity (95% CI), % | 29.2 | (29.0–29.4) | 29.6 | (29.4–29.8) |
Specificity (95% CI), % | 99.2 | (99.0–99.4) | 99.1 | (98.9–99.2) |
FPR (95% CI), % | 0.8 | (0.6–1.0) | 0.9 | (0.8–1.1) |
PPV (95% CI), % | 99.8 | (99.8–99.9) | 99.8 | (99.8–99.8) |
NPV (95% CI), % | 8.2 | (7.8–8.7) | 8.6 | (8.1–9.0) |
AUC (95% CI) | 0.904 | (0.902–0.905) | 0.889 | (0.887–0.891) |
AUC, area under the receiver operating curve; CI, confidence interval; FPR, false-positive rate; PPV, positive predictive value; NPV, negative predictive value; TOR, termination-of-resuscitation
The classification accuracy of the modified Goto’s TOR rule in predicting 1-month unfavourable neurological outcomes is shown in Table 3. The rates of CPC categories 1–2 in patients who met all four criteria for the modified Goto’s TOR rule were 0.04% and 0.05% in the development and validation groups, respectively. The specificity of the modified Goto’s TOR rule for the development and validation groups was 99.7%. The PPV of the modified Goto’s TOR rule for the development and validation groups was 99.9%.
Table 3.
Classification accuracy of modified Goto’s TOR rule for predicting 1-month unfavourable neurological outcome
Valuables | Development group (n = 231,363) | Validation group (n = 234,294) | ||
---|---|---|---|---|
Fulfilled 4/4 criteria | Did not fulfil criteria | Fulfilled 4/4 criteria | Did not fulfil criteria | |
(n = 63,528, 27.5%) | (n = 167,835, 72.5%) | (n = 65,104, 27.8%) | (n = 169,190, 72.2%) | |
CPC 3–5, n | 63,501 | 159,592 | 65,073 | 160,464 |
CPC 1–2, n | 27 | 8243 | 31 | 8,726 |
Rate of CPC 1–2 (95% CI), % | 0.04 (0.03–0.06) | 4.91 (4.81–5.02) | 0.05 (0.03–0.07) | 5.16 (5.05–5.26) |
Sensitivity (95% CI), % | 28.5 | (28.3–28.7) | 28.9 | (28.7–29.0) |
Specificity (95% CI), % | 99.7 | (99.5–99.8) | 99.7 | (99.5–99.8) |
FPR (95% CI), % | 0.3 | (0.2–0.5) | 0.3 | (0.2–0.4) |
PPV (95% CI), % | 99.9 | (99.8–99.9) | 99.9 | (99.9–99.9) |
NPV (95% CI), % | 4.9 | (4.5–5.4) | 5.2 | (4.7–5.6) |
AUC (95% CI) | 0.923 | (0.922–0.924) | 0.921 | (0.920–0.922) |
AUC, area under the receiver operating curve; CI, confidence interval; CPC, Cerebral Performance Category; FPR, false-positive rate; NPV, negative predictive value; PPV, positive predictive value; TOR, termination-of-resuscitation
Table 4 shows the external validation results of the three TOR rules after hospital arrival in predicting 1-month mortality using the validation group (n = 234,294). The specificity and PPV of the modified Goto’s TOR rule for predicting 1-month mortality were significantly higher than those of the other three TOR rules (all P < 0.001). The FPR of the modified Goto’s TOR rule for predicting 1-month mortality was significantly lower than that of the other three TOR rules (all P < 0.001). The survival rates in patients who met the KoCARC I and III rules (0.46% and 0.43%, respectively) were lower than 1%, but not in those who met the Goto’s TOR rule (1.07%). In addition, the specificity of Goto’s TOR rule was significantly lower than that of the KoCARC I and III rules (89.5% vs 95.5% and 96.3%, all P < 0.001, respectively). Therefore, the FPR of Goto’s TOR rule was higher than that of the KoCARC I and III rules: 10.5% vs 4.5% and 3.7%, respectively. The PPVs of Goto’s TOR rule and the KoCARC I and III rules were 98.9%, 99.5%, and 99.6%, respectively.
Table 4.
External validation of three TOR rules for predicting 1-month mortality (n = 234,294)
TOR rule in the emergency department | Goto's rule | KoCARC I rule | KoCARC III rule |
---|---|---|---|
Criteria | 1. Not witnessed by bystander | 1. Not witnessed by EMS | 1. Not witnessed by EMS |
2. Initial non-shockable rhythm | 2. Initial asystole | 2. Initial asystole | |
3. No prehospital ROSC | 3. No prehospital shock | 3. No prehospital shock | |
4. No prehospital ROSC | 4. No prehospital ROSC | ||
5. Age >60 years |
Valuables | Fulfilled criteria | Did not fulfill criteria | P value* | Fulfilled criteria | Did not fulfill criteria | P value* | Fulfilled criteria | Did not fulfill criteria | P value* |
---|---|---|---|---|---|---|---|---|---|
Death, n | 141,493 | 78,161 | 142,911 | 76,743 | 124,613 | 95,041 | |||
Survival, n | 1540 | 13,100 | 656 | 13,984 | 544 | 14,096 | |||
Survival rate (95% CI), % | 1.07 | 14.40 | 0.46 | 15.40 | 0.43 | 12.90 | |||
(1.02–1.13) | (14.1–14.6) | (0.42–0.49) | (15.2–15.7) | (0.40–0.47) | (12.7–13.1) | ||||
Sensitivity (95% CI), % | 64.4 | (64.2–64.6) | < 0.001 | 65.1 | (64.9–65.3) | < 0.001 | 56.7 | (56.5–56.9) | < 0.001 |
Specificity (95% CI), % | 89.5 | (89.0–90.0) | < 0.001 | 95.5 | (95.2–95.8) | < 0.001 | 96.3 | (96.0–96.6) | < 0.001 |
FPR (95% CI), % | 10.5 | (10.0–11.0) | < 0.001 | 4.5 | (4.2–4.8) | < 0.001 | 3.7 | (4.2–4.8) | < 0.001 |
PPV (95% CI), % | 98.9 | (98.9–90.0) | < 0.001 | 99.5 | (99.5–99.6) | < 0.001 | 99.6 | (99.5–99.6) | < 0.001 |
NPV (95% CI), % | 14.4 | (13.8–15.0) | < 0.001 | 15.4 | (14.8–16.0) | < 0.001 | 12.9 | (12.4–13.5) | < 0.001 |
AUC (95% CI) | 0.875 | (0.874–0.876) | NA | 0.897 | (0.896–0.898) | NA | 0.898 | (0.896–0.899) | NA |
AUC, area under the receiver operating curve; CI, confidence interval; EMS, emergency medical services; FPR, false-positive rate; KoCARC, Korean Cardiac Arrest Research Consortium; NA, not available; NPV, negative predictive value; PPV, positive predictive value; ROSC, return of spontaneous circulation; TOR, termination-of-resuscitation
*Compared with the modified Goto's rule
Table 5 shows the external validation results of the three TOR rules after hospital arrival in predicting 1-month unfavourable neurological outcomes using the validation group (n = 234,294). The specificity and PPV of the modified Goto’s TOR rule for predicting 1-month CPC 3–5 were significantly higher than those of the other three TOR rules (all P < 0.001). The FPR of the modified Goto’s TOR rule for predicting 1-month CPC 3–5 was significantly lower than that of the other three TOR rules (all P < 0.001). The rates of CPC 1–2 in patients who met the three TOR rules were < 1%. The specificity of Goto’s TOR rule (93.5%) was significantly lower than those of KoCARC I (98.6%) and III (98.8%): all P < 0.001. Therefore, the FPR of Goto’s TOR rule (6.5%) was higher than those of KoCARC I (1.4%) and III (1.2%). The PPVs of all the three TOR rules were > 99%.
Table 5.
External validations of three TOR rules for predicting 1-month unfavourable neurological outcome (n = 234,294)
TOR rule in the emergency department | Goto's rule | KoCARC I rule | KoCARC III rule |
---|---|---|---|
Criteria | 1. Not witnessed by bystander | 1. Not witnessed by EMS | 1. Not witnessed by EMS |
2. Initial non-shockable rhythm | 2. Initial asystole | 2. Initial asystole | |
3. No prehospital ROSC | 3. No prehospital shock | 3. No prehospital shock | |
4. No prehospital ROSC | 4. No prehospital ROSC | ||
5. Age >60 years |
Valuables | Fulfilled criteria | Did not fulfill criteria | P value* | Fulfilled criteria | Did not fulfill criteria | P value* | Fulfilled criteria | Did not fulfill criteria | P value* |
---|---|---|---|---|---|---|---|---|---|
CPC 3–5, n | 142,462 | 83,075 | 143,445 | 82,092 | 125,054 | 100,483 | |||
CPC 1–2, n | 571 | 8186 | 122 | 8635 | 103 | 8654 | |||
Proportion of patients with CPC 1–2 (95% CI), % | 0.40 | 8.97 | 0.09 | 9.50 | 0.08 | 7.90 | |||
(0.37–0.43) | (8.8–9.2) | (0.07–0.10) | (9.3–9.7) | (0.07–0.10) | (7.7–8.1) | ||||
Sensitivity (95% CI), % | 63.2 | (63.0–63.4) | < 0.001 | 63.6 | (63.4–63.8) | < 0.001 | 55.5 | (55.2–55.7) | < 0.001 |
Specificity (95% CI), % | 93.5 | (92.9–94.0) | < 0.001 | 98.6 | (98.3–98.8) | < 0.001 | 98.8 | (98.6–99.0) | < 0.001 |
FPR (95% CI), % | 6.5 | (6.0–7.1) | < 0.001 | 1.4 | (1.2–1.7) | < 0.001 | 1.2 | (1.0–1.4) | < 0.001 |
PPV (95% CI), % | 99.6 | (99.6–99.6) | < 0.001 | 99.9 | (99.9–99.9) | < 0.001 | 99.9 | (99.9–99.9) | < 0.001 |
NPV (95% CI), % | 9.0 | (8.4–9.6) | < 0.001 | 9.5 | (8.9–10.2) | < 0.001 | 7.9 | (7.4–8.5) | < 0.001 |
AUC (95% CI) | 0.901 | (0.900–0.903) | NA | 0.920 | (0.920–0.921) | NA | 0.920 | (0.920–0.920) | NA |
AUC, area under the receiver operating curve; CI, confidence interval; CPC, Cerebral Performance Category; EMS, emergency medical services; FPR, false-positive rate; KoCARC, Korean Cardiac Arrest Research Consortium; PPV, positive predictive value; NA, not available; NPV, negative predictive value; ROSC, return of spontaneous circulation; TOR, termination-of-resuscitation
*Compared with the modified Goto’s rule
Sensitivity analysis was performed after mean value imputation (23.4 min) of the missing data (n = 7,609, 3.0%) for EMS-CPR duration. The sensitivity analysis results are shown in Additional file 1: Results of sensitivity analysis for predicting 1-month mortality and unfavourable neurological outcome, Tables S1 and S2. The specificity and PPV of the modified Goto’s TOR rule for predicting 1-month mortality were 99.1% (95% CI 98.9–99.2%) and 99.8% (95% CI 99.8–99.8%), respectively, which were significantly higher than those of the other three TOR rules (Additional file 1: Table S1: Sensitivity analysis for predicting 1-month mortality (n = 250,517), all P < 0.001). The same was true in predicting 1-month CPC 3–5 (Additional file 1: Table S2; Sensitivity analysis for predicting 1-month unfavourable neurological outcome (n = 250,517)).
Discussion
In this nationwide, population-based observational study in Japan, we developed and validated a modified Goto’s TOR rule to guide physicians in deciding whether to terminate resuscitation in patients with refractory OHCA immediately after arrival at the emergency department. A modified Goto’s TOR rule was defined to meet the following four criteria: (1) initial asystole, (2) unwitnessed arrest by any layperson, (3) EMS-CPR duration > 20 min, and (4) no prehospital ROSC. Figure 3 shows a flow chart algorithm of how the modified Goto’s TOR rule should be applied. If a patient with OHCA meets all four criteria immediately after arrival at the emergency department, the physician-in-charge should consider terminating resuscitation before performing further resuscitation efforts. Our results demonstrated that the modified Goto’s TOR rule had a specificity of 99.1%, FPR of 0.9%, and PPV of 99.8% for predicting 1-month mortality in the validation group. Moreover, patients who met the modified Goto’s TOR rule had a 1-month survival rate of less than 1% (0.17% and 0.21% in the development and validation groups, respectively), commonly regarded as medical futility [4, 22, 23]. Using the validation data set, we compared the classification accuracy of the three TOR rules (Goto’s TOR [12], KoCARC I [11], and III rules [11]) in the emergency department with that of the modified Goto’s TOR rule in predicting 1-month mortality. The modified Goto’s TOR rule had a higher specificity and PPV than the other three TOR rules in predicting 1-month mortality. These findings suggest that the modified Goto’s TOR rule is preferable to Goto’s TOR and KoCARC I and III rules. When applying the modified Goto’s TOR rule immediately after hospital arrival in the emergency department, CPR efforts could be terminated in approximately 30% of patients without advanced life support in the hospital. Unlike the international TOR rules for EMS personnel [25], the modified Goto’s TOR rule presents no burden to EMS personnel in determining the futility of CPR for patients with OHCA. Since EMS personnel in Japan do not have the authority to decline resuscitation at the scene except death, the modified Goto’s TOR rule for physicians in the emergency department is suitable for its legal authorisation.
Fig. 3.
Flow chart algorithm of the modified Goto’s termination-of-resuscitation rule for emergency department physicians. CPR, cardiopulmonary resuscitation; EMS, emergency medical service; ROSC, return of spontaneous circulation
In 2013, we analysed data from the All-Japan Utstein Registry during 2005–2009 to develop and validate a TOR rule for emergency physicians immediately after hospital arrival to better utilise hospital healthcare resources [12]. There have been significant changes in the treatment of OHCAs since the original derivation of Goto’s TOR rule. External validation studies for Goto’s TOR rule showed a relatively low specificity of 94.8% (95% CI 92.7–96.4%) [13] or 95.0% (92.8–96.7%) [14] for predicting 1-month mortality compared with other TOR rules in the emergency department (SOS-KANTO 3 [13] and Lee’s rules [14]). This study also showed a lower specificity of Goto’s TOR rule with 89.5% (95% CI 89.0–90.0%) for predicting 1-month mortality compared with other TOR rules (Table 4). This may partly be explained by the improvement in the 1-month survival rate after OHCA in Japan, from 3.9% (2005–2009) [12] to 6.3% (Table 1. 2016–2019). Therefore, modified Goto’s TOR rule for physicians should be modified periodically with the emergence of new treatments and the evolution of social systems.
The SOS-KANTO 2012 study group [13] and Lee et al. [14] developed TOR rules after hospital arrival in 2017 and 2019, respectively. The SOS-KANTO 3 TOR rule includes three criteria: unwitnessed bystanders, asystole in the field, and emergency department [13]. Lee’s TOR rule was a combination of unwitnessed bystanders, no prehospital ROSC, and asystole in the emergency department [14]. Both rules include unwitnessed arrests by bystanders and asystole in the emergency department as a criterion. The specificities of these TOR rules were 98.6% (97.3–99.4%) [13] and 98.0 (96.4–99.0%) [14] for predicting 1-month mortality. In this study, we could not validate these two TOR rules because of the lack of rhythm data from the All-Japan Utstein Registry in the emergency department. However, the modified Goto’s TOR rule had higher specificity (> 99%) for predicting 1-month mortality in the development and validation groups.
Prehospital EMS-CPR duration is a critical factor associated with survival after OHCA [17, 18]. To date, there have been no TOR rules in the emergency department that include EMS-CPR duration as a criterion. However, the AHA 2010, 2015, and 2020 guidelines support the use of validated TOR rules in the field [25, 27, 28]. The universal TOR Guidelines state that resuscitation can be discontinued in the field by prehospital providers if the following three criteria are met: unwitnessed by EMS providers, no ROSC, and no shocks delivered at any time prior to transport [25]. In North America, it was found that application of the universal TOR Guidelines at 20 min of resuscitation in the field was able to predict futility, identifying 99.3% of survivors and 99.6% with good functional outcomes [29]. In this study, application of the modified Goto’s TOR rule identified 99.1% of survivors (Table 2) and 99.6% of neurologically intact survivors (Table 3). Accordingly, the modified Goto’s TOR rule in the emergency department, including EMS-CPR duration > 20 min, accurately identified potential OHCA survivors, similar to the universal TOR guidelines in the field.
This observational study has several limitations. First, the modified Goto’s TOR rule misclassified 137 survivors in the present validation study, resulting in a misclassification rate of 0.21% (137/65,104). Thirty-one patients (22.6%) were documented to have neurologically intact survival. Unfortunately, we were unable to determine the factors contributing to the outcomes of these patients because we could not access the original patient records. Nevertheless, the modified Goto’s TOR rule had a PPV of 99.8% for predicting 1-month mortality, which is within the acceptable range used by medical ethicists for defining futility [4, 24, 25, 29]. Second, although end-tidal CO2 < 10 mmHg after 20 min of resuscitation was found to be predictive of futility [28], we did not analyse the results of end-tidal CO2 monitoring because of the lack of data in the registry. Third, patients who met the modified Goto’s TOR rule after hospital arrival and achieved in-hospital ROSC but did not survive in the emergency department would be candidates for organ donors as an important ancillary benefit of refractory OHCAs. However, we could not analyse the rates of in-hospital ROSC among patients who met the TOR rules owing to a lack of in-hospital data. Fourth, although we used a uniform data collection procedure, a large sample size, and a population-based design, we cannot exclude the possibility of uncontrolled confounders that could have influenced the outcomes, such as pre-existing comorbidities, location of the arrest, quality of bystander CPR or EMS-initiated CPR, and in-hospital treatments, because the study was retrospective and observational. In addition, the extent to which poor outcomes were driven by a self-fulfilling prophecy bias was unknown. Fifth, as with all epidemiological studies, selection bias may have occurred, and the data may have lacked integrity and validity. Finally, the relevance of our results to other communities with different emergency care systems and protocols remains unclear. In particular, in some Asian countries where the TOR rule in the field is not allowed, a validation study for the modified Goto’s TOR rule in the emergency department is required before implementation.
Conclusions
The modified Goto’s TOR rule (which includes the following four criteria: initial asystole, unwitnessed arrest, EMS-CPR duration > 20 min, and no prehospital ROSC) with a > 99% predictor of 1-month mortality is a reliable tool for physicians treating refractory OHCAs immediately after hospital arrival.
Supplementary Information
Additional file 1.Results of sensitivity analysis for predicting 1-month mortality and unfavourable neurological outcome (n = 250,517)
Acknowledgements
We would like to thank all EMS personnel and participating physicians in Japan and the FDMA for their generous cooperation in establishing and maintaining the database.
Abbreviations
- AHA
American Heart Association
- AUC
Area under the receiver operating curve
- CI
Confidence interval
- CoSTR
International consensus on cardiopulmonary resuscitation and emergency cardiovascular care science with treatment recommendations
- CPC
Cerebral performance category
- CPR
Cardiopulmonary resuscitation
- EMS
Emergency medical service
- FDMA
Fire and Disaster Management Agency
- FPR
False-positive rate
- KoCARC
Korean Cardiac Arrest Research Consortium
- NPV
Negative predictive value
- OHCA
Out-of-hospital cardiac arrest
- PPV
Positive predictive value
- ROSC
Return of spontaneous circulation
- TOR
Termination-of-resuscitation
Author contributions
YG involved in conceptualisation; AF involved in data curation, writing—review, and editing; TM involved in data curation; YG involved in data curation, formal analysis, writing—review and editing; YG involved in formal analysis, writing—first draft. All authors have read and approved the final manuscript.
Funding
This work was supported by the Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research, Grant Nos. 20H202271 and 21K10324).
Availability of data and materials
The datasets generated and analysed during the current study are not publicly available because of the Fire and Disaster Management Agency (FDMA) regulations but are available from the corresponding author upon reasonable request.
Declarations
Ethics approval and consent to participate
This study was approved by the institutional review board of Kanazawa University (No. 1263-9). The requirement for written informed consent was waived because of the use of anonymised data.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Mancini ME, Soar J, Bhanji F, Billi JE, Dennett J, Finn J, et al. Part 12: education, implementation, and teams. 2010 International consensus on cardiopulmonary resuscitation and emergency cardiovascular care science with treatment recommendations. Circulation. 2010;122:S539–81. [DOI] [PubMed]
- 2.Soar J, Mancini ME, Bhanji F, Billi JE, Dennett J, Finn J, et al. Part 12: education, implementation, and teams: 2010 international consensus on cardiopulmonary resuscitation and emergency cardiovascular care science with treatment recommendations. Resuscitation. 2010;81:e288–330. doi: 10.1016/j.resuscitation.2010.08.030. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Morrison LJ, Visentin LM, Kiss A, Theriault R, Eby D, Vermeulen M, et al. Validation of a rule for termination of resuscitation in out-of-hospital cardiac arrest. N Engl J Med. 2006;17:478–487. doi: 10.1056/NEJMoa052620. [DOI] [PubMed] [Google Scholar]
- 4.Sasson C, Hegg AJ, Macy M, Park A, Kellermann A, McNally B. Prehospital termination of resuscitation in cases of refractory out-of-hospital cardiac arrest. JAMA. 2008;17:1432–1438. doi: 10.1001/jama.300.12.1432. [DOI] [PubMed] [Google Scholar]
- 5.Skrifvars MB, Vayrynen T, Kuisma M, Castren M, Parr MJ, Silfverstople J, et al. Comparison of Helsinki and European Resuscitation Council “do not attempt to resuscitate” guidelines, and a termination of resuscitation clinical prediction rule for out-of-hospital cardiac arrest patients found in asystole or pulseless electrical activity. Resuscitation. 2010;17:679–684. doi: 10.1016/j.resuscitation.2010.01.033. [DOI] [PubMed] [Google Scholar]
- 6.Greif R, Bhanji F, Bigham BL, Bray J, Breckwoldt J, Cheng A, et al. Education, implementation, and teams. 2020 International consensus on cardiopulmonary resuscitation and emergency cardiovascular care science with treatment recommendations. Circulation 2020;142:S222–83. [DOI] [PubMed]
- 7.Goto Y, Funada A, Maeda T, Okada H, Goto Y. Field termination-of-resuscitation rule for refractory out-of-hospital cardiac arrests in Japan. J Cardiol. 2019;73:240–246. doi: 10.1016/j.jjcc.2018.12.002. [DOI] [PubMed] [Google Scholar]
- 8.Jung H, Lee MJ, Cho JW, Lee SH, Lee SH, Mun YH, et al. External validation of multimodal termination of resuscitation rules for out-of-hospital cardiac arrest patients in the COVID-19 era. Scand J Trauma Resusc Emerg Med. 2021;29:19. doi: 10.1186/s13049-021-00834-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Ong ME, Cho J, Ma MH, Tanaka H, Nishiuchi T, Sakaf OA, et al. Comparison of emergency medical services systems in the pan-Asian resuscitation outcomes study countries: report from a literature review and survey. Emerg Med Australas. 2013;25:55–63. doi: 10.1111/1742-6723.12032. [DOI] [PubMed] [Google Scholar]
- 10.Chiang WC, Ko PC, Chang AM, Liu SS, Wang HC, Yang CW, et al. Predictive performance of universal termination of resuscitation rules in an Asian community: are they accurate enough? Emerg Med J. 2015;32(4):318–323. doi: 10.1136/emermed-2013-203289. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Yoon JC, Kim YJ, Ahn S, Jin YH, Lee SW, Song KJ, et al. Factors for modifying the termination of resuscitation rule in out-of-hospital cardiac arrest. Am Heart J. 2019;213:73–80. doi: 10.1016/j.ahj.2019.04.003. [DOI] [PubMed] [Google Scholar]
- 12.Goto Y, Maeda T, Goto YN. Termination-of-resuscitation rule for emergency department physicians treating out-of-hospital cardiac arrest patients: an observational cohort study. Crit Care. 2013;17:R235. doi: 10.1186/cc13058. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.SOS–KANTO 2012 Study Group. A new rule for terminating resuscitation of out-of-hospital cardiac arrest patients in Japan: a prospective study. J Emerg Med. 2017;53:345–52. [DOI] [PubMed]
- 14.Lee DE, Lee MJ, Ahn JY, Ryoo HW, Park J, Kim WY, et al. New termination-of-resuscitation models and prognostication in out-of-hospital cardiac arrest using electrocardiogram rhythms documented in the field and the emergency department. J Korean Med Sci. 2019;34:e134. doi: 10.3346/jkms.2019.34.e134. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Callaway CW, Donnino MW, Fink EL, Geocadin RG, Golan E, Kern KB, et al. Part 8: post–cardiac arrest care: 2015 American Heart Association guidelines update for cardiopulmonary resuscitation and emergency cardiovascular care. Circulation. 2015;132:465–482. doi: 10.1161/CIR.0000000000000262. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Sandroni C, Cariou A, Cavallaro F, Cronberg T, Friberg H, Hoedemaekers C, et al. Prognostication in comatose survivors of cardiac arrest: an advisory statement from the European Resuscitation Council and the European Society of Intensive Care Medicine. Resuscitation. 2014;85:1779–1789. doi: 10.1016/j.resuscitation.2014.08.011. [DOI] [PubMed] [Google Scholar]
- 17.Goto Y, Funada A, Goto Y. Relationship between the duration of cardiopulmonary resuscitation and favorable neurological outcomes after out-of-hospital cardiac arrest: a prospective, nationwide, population-based cohort study. J Am Heart Assoc. 2016;5:e002819. doi: 10.1161/JAHA.115.002819. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Funada A, Goto Y, Tada H, Teramoto R, Shimojima M, Hayashi K, Kawashiri MA, et al. Duration of cardiopulmonary resuscitation in patients without prehospital return of spontaneous circulation after out-of-hospital cardiac arrest: results from a severity stratification analysis. Resuscitation. 2018;124:69–75. doi: 10.1016/j.resuscitation.2018.01.008. [DOI] [PubMed] [Google Scholar]
- 19.Goto Y, Funada A, Goto Y. Impact of prehospital physician-led cardiopulmonary resuscitation on neurologically intact survival after out-of-hospital cardiac arrest: a nationwide population-based observational study. Resuscitation. 2019;136:38–46. doi: 10.1016/j.resuscitation.2018.11.014. [DOI] [PubMed] [Google Scholar]
- 20.Ambulance service planning office of Fire and Disaster Management Agency of Japan. Effect of first aid for cardiopulmonary arrest [in Japanese]. https://www.fdma.go.jp/publication/rescue/items/kkkg_r01_01_kyukyu.pdf. Accessed 26 Feb 2022.
- 21.Japan Resuscitation Council CPR Guidelines Committee. 2015 Japanese guidelines for emergency care and cardiopulmonary resuscitation. Tokyo: Igaku Shoin; 2016 (in Japanese).
- 22.Perkins GD, Jacobs IG, Nadkarni VM, Bhanji F, Bossaert LL, Chamberlain D, et al. Cardiac arrest and cardiopulmonary resuscitation outcome reports: update of the utstein resuscitation registry templates for out-of-hospital cardiac arrest: a statement for healthcare professionals from a task force of the International Liaison Committee on Resuscitation (American Heart Association, European Resuscitation Council, Australian and New Zealand Council on Resuscitation, Heart and Stroke Foundation of Canada, InterAmerican Heart Foundation, Resuscitation Council of Southern Africa, Resuscitation Council of Asia); and the American Heart Association Emergency Cardiovascular Care Committee and the Council on Cardiopulmonary, Critical Care. Perioper Resuscit Circulat. 2015;132:1286–1300. doi: 10.1161/CIR.0000000000000144. [DOI] [PubMed] [Google Scholar]
- 23.Goto Y, Maeda T, Goto Y. Decision-tree model for predicting outcomes after out-of-hospital cardiac arrest in the emergency department. Crit Care. 2013;17:R133. doi: 10.1186/cc12812. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Schneiderman LJ. Defining medical futility and improving medical care. J Bioeth Inq. 2011;8:123–131. doi: 10.1007/s11673-011-9293-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Morrison LJ, Kierzek G, Diekema DS, Sayre MR, Silvers SM, Idris AH, et al. Part 3: ethics. 2010 American Heart Association guidelines for cardiopulmonary resuscitation and emergency cardiovascular care. Circulation. 2010;122: S665-75. [DOI] [PubMed]
- 26.Hess EP, Brison RJ, Perry JJ, Calder LA, Thiruganasambandamoorthy V, Agarwal D, et al. Development of a clinical prediction rule for 30-day cardiac events in emergency department patients with chest pain and possible acute coronary syndrome. Ann Emerg Med. 2012;59:115–125. doi: 10.1016/j.annemergmed.2011.07.026. [DOI] [PubMed] [Google Scholar]
- 27.Mancini ME, Diekema DS, Hoadley TA, Kadlec KD, Leveille MH, McGowan JE, et al. Part 3: ethical issues: 2015 American Heart Association guidelines update for cardiopulmonary resuscitation and emergency cardiovascular care. Circulation. 2015;132:S383–S396. doi: 10.1161/CIR.0000000000000254. [DOI] [PubMed] [Google Scholar]
- 28.Panchal AR, Bartos JA, Cabañas JG, Donnino MW, Drennan IR, Hirsch KG, et al. Part 3: adult basic and advanced life support: 2020 American Heart Association guidelines update for cardiopulmonary resuscitation and emergency cardiovascular care. Circulation. 2020;142:S366–468. doi: 10.1161/CIR.0000000000000916. [DOI] [PubMed] [Google Scholar]
- 29.Drennan IR, Case E, Verbeek PR, Reynolds JC, Goldberger ZD, Jasti J, et al. A comparison of the universal TOR guideline to the absence of prehospital ROSC and duration of resuscitation in predicting futility from out-of-hospital cardiac arrest. Resuscitation. 2017;111:96–102. doi: 10.1016/j.resuscitation.2016.11.021. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Additional file 1.Results of sensitivity analysis for predicting 1-month mortality and unfavourable neurological outcome (n = 250,517)
Data Availability Statement
The datasets generated and analysed during the current study are not publicly available because of the Fire and Disaster Management Agency (FDMA) regulations but are available from the corresponding author upon reasonable request.